Risks to Data Sharing and Data Ownership Peer Reviewed

Abstract

The aims of this paper are to illustrate the trend towards data sharing, i.e. the regulated availability of the original patient-level data obtained during a report, and to talk over the expected advantages (pros) and disadvantages (cons) of data sharing in radiological research. Expected pros include the potential for verification of original results with alternative or supplementary analyses (including estimation of reproducibility), advocacy of knowledge past providing new results by testing new hypotheses (not explored past the original authors) on pre-existing databases, larger scale analyses based on individual-patient data, enhanced multidisciplinary cooperation, reduced publication of false studies, improved clinical do, and reduced cost and time for clinical research. Expected cons are outlined as the chance that the original authors could not exploit the entire potential of the information they obtained, possible failures in patients' privacy protection, technical barriers such as the lack of standard formats, and possible data misinterpretation. Finally, open bug regarding data ownership, the role of individual patients, advocacy groups and funding institutions in decision making about sharing of data and images are discussed.

Key Points

• Regulated availability of patient-level data of published clinical studies (data-sharing) is expected.

• Expected benefits include verification/advancement of knowledge, reduced cost/time of research, clinical improvement.

• Potential drawbacks include faults in patients' identity protection and information misinterpretation.

Introduction

In clinical research, spontaneous data sharing is not notwithstanding equally common as it is in other fields such as genetics, astronomy or physics [ane]. However, the concept of data sharing has been suggested for many reasons, including the patient-centred nature of medical research and healthcare and the expectation that noesis from existing information should be maximized to benefit all stakeholders.

Although a transition to data sharing is a procedure that will have time and planning, those who prefer the principles and practices of open scientific discipline will likely do good from it [ii, 3]. In addition, the emergence of information sharing as a potential requirement by some agencies and journals warrants attending by the imaging community. Indeed, from July 1st, 2018 the International Committee of Medical Periodical Editors (ICMJE) will require a data sharing argument as a condition of consideration for publication of clinical trials [4].

In this commodity, nosotros discuss potential advantages and disadvantages of data sharing.

From open up-admission to data sharing

A trend towards larger accessibility to scientific medical knowledge is already visible in the progressive tendency of medical journals in ensuring the open-admission option, in which the authors or their institutions pay an article-level fee to guarantee the immediate gratis availability of their papers [five].

In Table ane we study the policies of all the 18 general imaging journals on access and information sharing [6,vii,eight,9,ten,eleven,12,13,14,15,16,17]. This was derived from the electric current Thomson Reuters list – Radiology, Nuclear Medicine, and Medical Imaging. For comparison, the 17 most-impacted general medicine journals were selected from the current Thomson Reuters list – Medicine, General and Internal [xviii,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35]. Among the 18 imaging journals, four are open access, 12 offer open access as an option (Radiology provides gratis admission 12 months after publication), and two practise not offering an open-access option. Amid the 17 medical journals, vi are open access (The Medical Periodical of Australia only for research manufactures and case reports), eight offer open access as an selection (Periodical of the American Medical Clan [JAMA] provides free access 6 months after publication), two do not offer an open up access option, and i (The New England Journal of Medicine [NEJM]) provides free admission to research articles half-dozen months after publication. Thus, the open access option is currently widely adopted by both general imaging journals (11/18) and full general medicine journals (8/17).

Table 1 Policies on access and data repository or sharing by major full general imaging journals and major general medicine journals

Full size table

The practice of information sharing entails much more than than open access. It is the regulated availability of the original participant-past-participant data obtained during a written report, which may include data not yet analysed. Amidst the eighteen general imaging journals, data sharing is not even mentioned by 12 journals, encouraged by three, mandatory only upon asking in two, and requested past one. Among the 17 general medicine journals, it is non mentioned past vii journals, encouraged past six, requested by three (NEJM but for data obtained by microarray), and considered mandatory only upon request past one (Table one). In practise, data repository or sharing is currently not mentioned in the instructions for authors of the bulk of general imaging journals (14/18) and major full general medicine journals (10/17). Despite private journals exercise not mention whatever policy on data sharing, some publishers such as Elsevier have their own general suggestions, which refer to Open Access [viii], even though not immediately visible to the authors when they submit a manuscript. When data sharing is encouraged, authors are informed they should be prepared to provide original study information if requested past the editors.

In contempo years, several funding bodies declared the necessity for information sharing. In 2015, the U.South. National Institutes of Health (NIH) expressed its intention to request making the digital information from NIH-funded studies publicly available [36]. Regulatory agencies, specifically the European Medicines Bureau, have requested greater data sharing past companies manufacturing drugs and clinical devices. Influential organizations such as the World Wellness Arrangement and the U.S. National Academy of Medicine published reports asking for responsible sharing of information from clinical trials [37]. As well, several foundations, for instance the Alfred P. Sloan Foundation [38], the Bill and Melinda Gates Foundation [39], the Ford Foundation [40], the Gordon and Betty Moore Foundation [41], and the National Science Foundation [42], require data sharing and data management plans for all research grant proposals.

The pharmaceutical manufacture too plays a role in promoting information sharing. The Yale University Open Data Access (YODA) project [43] performs independent scientific review of investigators' requests for pharmaceutical and medical data from clinical trials on devices marketed by Johnson & Johnson, including both total clinical written report reports and participant-level information. Notably, the YODA project has obtained permission to make independent decisions about the release of Johnson & Johnson's clinical trial data. This project establishes a procedure in which requests are judged fairly and decisions are made by an independent academic partner, a model that could be applied to other fields of medicine [44].

Another example is the Academic Research Organization Consortium for Continuing Evaluation of Scientific Studies – Cardiovascular (Admission CV) [45]. They propose a secure method for sharing patient-sensitive data that combines the protection of patients' identity with the legitimate desire of the scientific community for data access and the viewpoint of the researchers who created the database. This approach consists of the following steps: (1) After publication of the primary results of a trial, researchers interested in the study information may send a request to the trial's publication committee; (2) Twenty-four months later the publication of the primary study, requests should be considered by a review group composed of members of Admission CV not involved in the trial, the trial principal investigator, a trial statistician, and a member of the data and safe monitoring lath. This committee evaluates all proposals to approve those that are feasible, hypothesis-based, non-duplicative, and guided by investigators with technical capability and a plan for publication. The period of 24 months is called to secure the database and to allow the original investigators to perform their own pre-planned secondary analyses; (3) All requests and subsequent decisions will be posted on an Admission CV Web portal, ideally within 60 days [45].

In the field of radiology, information sharing too means accessibility to medical images. Indeed, "Images are more pictures, they are information" [46]. This implies access to the images produced in a given study for boosted reading, interpretation, and extraction. To this stop, several image repositories were created. An case is the XNAT Central [47, 48], a publicly attainable information repository based on the XNAT open-source platform which hosts a broad variety of research imaging datasets, especially from neuroimaging, but also from oncology, orthopaedics and cardiology. Other examples are The Cancer Imaging Archive [49] and the Lung Image Database Consortium [50].

Such repositories may exist very helpful in several fields, especially for image biomarker development, radiomics and machine learning, each field enervating different approaches. Moreover, the integration, standardization and analysis of these data poses a large challenge, the solution to which may exist addressed using cerebral calculating. An instance of cognitive computing is the system adult by IBM named Watson (IBM Watson Health Imaging, Armonk, NY, United states of america). Information technology strives to organize bachelor data and nowadays information technology in a contextually relevant, probability-driven manner to assistance healthcare professionals in an objective fashion, whether at a reading workstation or at the signal-of-care [51]. An of import change is underway. To make datasets from medical enquiry publicly available in a timely fashion requires regulations that maximize the benefits and minimize the risks [52, 53]. Indeed, information sharing provides a potential for stimulating new ideas, avoiding duplication of trials, and raise transparency [36, 54,55,56,57] also as increasing collaboration and interdisciplinary research [i, 58, 59]. Withal, at the same fourth dimension, sharing clinical data presents some risks, burdens and challenges such as the demand to preserve the privacy of patients, to defend the legitimate economical interests of the sponsors, and to guard against invalid secondary analyses potentially undermining trust in clinical trials or otherwise harming public health [36, 37, 53, 60].

Potential benefits of information sharing

These can be subdivided into: (i) verification and advancement in knowledge; (ii) reduced cost and time for clinical inquiry; and (three) clinical improvement (Fig. ane).

Fig. 1

Expected pros and cons of data sharing. IPD individual patient data meta-analyses

Total size paradigm

Verification and advancement in knowledge

The first potential implication of data-sharing is the verification past independent authors of the results presented in a given publication. When data are shared, they may be used by other researchers to perform alternative or supplementary analyses. This '2nd-hand' analysis may testify results in support of the initial findings or could reveal errors or inconsistencies in the original research, or could place bug needing extended analysis.

In other cases, data sharing tin allow elucidation of new results. New findings can be disclosed starting from hypotheses not considered past the original written report team. New insights can be presented from existing data simply non yet analysed in the original publication(southward). As well, investigators may be interested in performing the analysis of datasets coming from various sources to enhance precision, i.e. to perform reproducibility analyses beyond different databases, regarding established theories or new hypotheses. In fact, reproducibility analysis is crucial for emergent topics in radiology such as standardization of imaging biomarkers, especially from magnetic resonance imaging [61]. The availability of databases from different studies could let for this gap to be filled and could help in translating new imaging biomarkers into clinical do [62]. In this regard, reproducibility assay could become 1 of the main advantages of data sharing.

The introduction of registries of patients afflicted with a defined illness could be considered a primitive grade of data sharing [63, 64], important not just for widespread diseases, such as cancers, but peculiarly for rare diseases.

Another approach of spontaneous information sharing is that underlying individual patient data meta-analyses [65]. Authors of an private patient data meta-analysis typically contact the authors of each eligible study asking to share their data, with the aim of creating a new unique individual-patient database. Of note, the power of the individual-patient data approach is higher than that of conventional (study-level) meta-analyses, which rely on complex statistical methods [66]. For instance, in a written report published past Marinovich et al. [67] on the agreement between MRI and pathological breast tumour size later on handling, a full of 24 studies (1,228 patients) were eligible for inclusion, but merely eight of these contributed to the individual-patient data assay for a total of 300 patients. Had regulated data sharing been in place, that private-patient data meta-assay would take included a much richer dataset. Moreover, data sharing could boost a wider adoption of wellness applied science assessment. Indeed, in the context of a new product evaluation, data sharing may be useful in the validation level, requiring a high number of information/images, rather than at the initial development level.

Another potential advantage of data sharing is to reduce the publication of false studies, specially when the information are intentionally falsified. Recently, 64 articles were retracted from x Springer journals subsequently editorial checks found fake email addresses, and subsequent internal investigations uncovered fabricated peer-review reports [68]. This retraction came merely a few months after BioMed Central had retracted 43 articles for the same reason; however, this phenomenon involved most major publishers such as likewise SAGE, Elsevier, Informa, and Lippincott Williams & Wilkins [69]. Information sharing might discourage information cosmos and manipulation, potentially more detectable in a complete database than in reported results.

Reduced cost and time for clinical research

Data sharing could potentially pb to an optimization of time and costs of clinical enquiry by preventing the duplication of trials [lxx, 71]. For example, costs for the stipulation of insurances for patients' coverage, the purchase of materials or the salaries of the staff responsible for information drove tin can be avoided. In improver, using an existing shared database, the new results could be obtained many years prior to those derived from a new clinical study.

Clinical improvement

An effect in terms of clearer evidence on the safety and effectiveness of diagnostic procedures and therapies, improving public healthcare [72,73,74], may exist considered the final aim of data sharing. To avoid the loss of findings contained in the original dataset and not used for the primary publication(s) could play a part in this direction [53]. Institutions sharing their data could obtain a more than comprehensive picture about the benefits and risks of a medical decision. Nevertheless, a existent clinical improvement from data sharing is a hypothesis that even so needs to be demonstrated.

Potential drawbacks from information sharing

The sharing of clinical databases raises several concerns (see Fig. ane). 1 of the reasons not to share data is that researchers are evaluated competitively, based on the quality and number of articles published during their career, so they may worry that other people will use their data and efforts to produce new publications. The potential for secondary analyses contradicting initially reported results may be a deterrent. Authors may not be willing to share data that had cost them great effort and resources. However, reciprocally, they would also straight benefit from using someone else's information.

Bierer et al. [75] recently suggested formalizing 'data authorship' as an incentive to information sharing: "as a matter of fairness and every bit a matter of providing an incentive for data sharing, the persons who initially gathered the information should receive appropriate and standardized credit that can be used for bookish advancement, for grant applications, and in broader situations".

Another business organisation is the potential for mistake in the patient identity protection caused by the transmission of sensitive information. Data must be de-identified: de-identification, non just anonymization, consists of transforming a dataset so that the dorsum identification of individuals becomes impossible or extremely hard. Dissimilar regulations may require dissimilar degrees of de-identification, particularly in the absence of informed consents specifying the possibility of data sharing. De-identification can be achieved with unlike types of data transformations that must ensure patient privacy without affecting data quality [76]. Nonetheless, the de-identified data do not eliminate all risks of re-identification. Moreover, the reduction of this risk to nada may destroy or significantly impair the utility of the data for subsequent assay or verification. For these reasons, the stipulation of Data Use Agreements (DUAs) is considered a useful strategy and best practice for increasing the benefits and mitigating the risks of clinical data sharing [77]. Specifically, DUAs address of import bug such as limitations on date usage, obligations to data safeguard, liability for impairment arising from information usage and publication, and privacy rights that are associated with transfer of confidential or protected information. In contrast, the U.S. Office for Man Research Protections stated that there is no need for separate consent from trial participants for the sharing of de-identified data [4].

A limitation to the adoption of information sharing can originate from technical barriers. The paradigm conformity is influenced by vendor, modality, and conquering parameters on the one hand; and by epitome mail-processing manufacturer, reconstruction parameters, and software versions, on the other hand. An example is represented by the use in magnetic resonance of arbitrary units that conspicuously depend on the specific vendor and model, making a between-study comparison impossible. A way to overcome this limitation could be a drastic standardization, with manufacturers defining new shared standards.

Another intrinsic barrier to data sharing could be the poor documentation of datasets, peculiarly if not documented in English. Moreover, important information about methodology might not be independent immediately in the database or immediately retrievable. All these issues should be considered when planning for potential data sharing of research.

To share or non to share?

In conclusion, in a world that moves towards greater transparency and privacy protection, information sharing stands between these two competing interests. Not all concerns on data sharing accept already been solved and many questions remain to exist addressed: Who is the rightful owner of the data? What is the role of private patients and advancement groups in determination making about sharing of data and images? Should Ethics Committees change their approach for written report approval? And how? What is the exact office of institutions, especially public ones, that funded the original report? Should patient advocacy groups and funding organizations be involved in decision making about data sharing? These issues must be regulated.

Despite all the higher up-described issues relating to data sharing, a transition to a more open up medical science has begun. If benefits of information sharing will be more and more perceived as prevailing over harms therefrom, this choice will win. Researchers and institutions who first seize this opportunity will be on the wave-front of an innovation likely to be in favour of patients and public wellness. Radiologists should be kept informed of this emerging issue. Information technology is time to share!

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Acknowledgements

This article has been promoted by the European Network for Assessment of Imaging in Medicine, a articulation initiative of the European Institute for Biomedical Imaging Research

(http://www.eibir.org/scientific-activities/joint-initiatives/euroaim/)

Funding

This article was supported by local research funds of the IRCCS Policlinico San Donato, a Clinical Research Hospital partially funded past the Italian Ministry of Health.

Author information

Affiliations

1. Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via L. Mangiagalli 31, 20133, Milan, Italy

   Francesco Sardanelli & Luca M. Sconfienza

2. Radiology Unit, IRCCS Policlinico San Donato, Via Morandi xxx, 20097, San Donato Milanese Milan, Italy

   Francesco Sardanelli & Giovanni Di Leo

3. PhD Course in Integrative Biomedical Research, Università degli Studi di Milano, Via L. Mangiagalli 31, 20133, Milan, Italy

   Marco Alì

4. Departments of Radiology and Epidemiology, Erasmus University Medical Eye, PO Box 2040, Rotterdam, The Netherlands

   Myriam Thou. Hunink

5. Department of Health Policy and Medicine, Harvard School of Public Health, Harvard University, 677 Huntington Avenue, Boston, MA, 02115, USA

   Myriam G. Hunink

6. Screening and Test Evaluation Programme, School of Public Health, Sydney Medical School, University of Sydney, Edward Ford Building, Room A27, Sydney, NSW, 2006, Australia

   Nehmat Houssami

7. Unit of Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Galeazzi, Via Riccardo Galeazzi 4, 20161, Milan, Italy

   Luca M. Sconfienza

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Correspondence to Francesco Sardanelli.

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Sardanelli, F., Alì, M., Hunink, M.1000. et al. To share or non to share? Expected pros and cons of information sharing in radiological research. Eur Radiol 28, 2328–2335 (2018). https://doi.org/10.1007/s00330-017-5165-5

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• Received: 01 August 2017

• Revised: 06 Oct 2017

• Accustomed: 31 October 2017

• Published: 18 January 2018

• Upshot Engagement: June 2018

• DOI : https://doi.org/10.1007/s00330-017-5165-v

Keywords

• Confidentiality
• Database
• Data sharing
• Information dissemination
• Radiology

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Source: https://link.springer.com/article/10.1007/s00330-017-5165-5

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